@article{ref1,
title="Analysis of human and organizational factors that influence mining accidents based on Bayesian network",
journal="International journal of occupational safety and ergonomics",
year="2018",
author="Mirzaei Aliabadi, Mostafa and Aghaei, Hamed and Kalatpour, Omid and Soltanian, Ali Reza and Nikravesh, Asghar",
volume="ePub",
number="ePub",
pages="1-8",
abstract="PURPOSE: The present study was aimed to analyze human and organizational factors involved in mining accidents and determine the relationships among these factors. <br><br>MATERIALS AND METHODS: In this study, Human Factors Analysis and Classification System (HFACS) with Bayesian network (BN) were combined in order to analyze contributing factors in mining accidents. BN was constructed based on a hierarchal structure of HFACS. The required data were collected from a total of 295 cases of Iranian mining accidents and analyzed using HFACS. Afterwards, prior probability of contributing factors was computed using the expectation-maximization algorithm. Sensitivity analysis was applied to determine which contributing factor had a higher influence on unsafe acts to select the best intervention strategy. <br><br>RESULTS: The analyses showed that skill based errors, routine violations, environmental factors, and planned inappropriate operation had a higher relative importance in the accidents. Moreover, sensitivity analysis revealed that environmental factors, failed to correct known problem, and personnel factors had a higher influence on unsafe acts. <br><br>CONCLUSION: The results of the present study could provide guidance to help safety and health management by adopting proper intervention strategies to reduce mining accidents.<p /> <p>Language: en</p>",
language="en",
issn="1080-3548",
doi="10.1080/10803548.2018.1455411",
url="http://dx.doi.org/10.1080/10803548.2018.1455411"
}